Disentangling estimands and the intention-to-treat principle
| Autor: | Ann-Kristin Leuchs, Andreas Brandt, Norbert Benda, Jörg Zinserling |
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| Rok vydání: | 2016 |
| Předmět: |
Statistics and Probability
Research design Computer science media_common.quotation_subject Population 01 natural sciences law.invention 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Randomized controlled trial law Econometrics Pharmacology (medical) 030212 general & internal medicine 0101 mathematics education media_common Pharmacology Selection bias education.field_of_study Actuarial science Intention-to-treat analysis Missing data Causality restrict |
| Zdroj: | Pharmaceutical Statistics. 16:12-19 |
| ISSN: | 1539-1604 |
| DOI: | 10.1002/pst.1791 |
| Popis: | Randomized controlled trials (RCTs) aim at providing reliable estimates of treatment benefit. Missing data and nonadherence to treatment are distinct problems that can substantially impede this task. In practice, the fact that the handling of missing data due to nonadherence affects the question that is addressed is often ignored. Estimands allow precisely predefining the question of interest. Estimands are definitions of that which is being estimated with regard to population, endpoint, and handling of postrandomization events (eg, nonadherence). Depending on the situation, different estimands are of relevance. Therefore, it is important that the intention-to-treat (ITT) principle, which is considered the gold standard for analyzing RCTs, does not restrict an RCT's primary objective to only one of several relevant estimands. Although much ambiguity is involved around what is considered to constitute the ITT principle, many associate ITT with completely following up all patients and including all data of all randomized patients as allocated into the analysis. This would restrict primary objectives to estimating the effect of treatment policy and is certainly not warranted in all situations. To maintain the advantage of having the clear recommendation to follow the ITT principle while allowing for various relevant estimands as primary objective, we argue that the appropriate way forward is to define ITT as including all randomized patients into the analysis set and each patient is to be allocated to his or her randomized treatment. This definition comprises the actual intent of ITT and can be fully implemented also in settings where complete follow-up is impossible. |
| Databáze: | OpenAIRE |
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